Evaluation of healthy and sensory indexes of sweetened beverages using an electronic tongue

Application of an electronic tongue for Tunisian olive oils’ classification according to olive cultivar or physicochemical parameters

“…Finally, in fewer situations, sensor and replica had different signal trend behaviors (positive and negative) resulting in a positive or negative sensitivity values for a specific polar compound. Based on these findings, it can be concluded that, in general, both sensor and sensor replica should be considered as independent sensors due to the probably slight different physical properties (e.g., transparency, porosity, permeability) that may occur due to the possible formation of inhomogeneous membrane surfaces, which could be attributed to the drop-by-drop membrane preparation technique [41]. The differences in the membrane surfaces of sensor and sensor replica may result in the occurrence of different adsorption phenomena and surface chemical reactions, which may lead to deviations in sensors' readings [42].…”

Monovarietal extra-virgin olive oil classification: a fusion of human sensory attributes and an electronic tongue

“…Although this methodology may be considered an overoptimistic procedure, the use of a more robust cross-validation approach (e.g., based on an external validation set) was not possible due to the large number of groups considered (eight monovarietal EVOOs) and the reduction in the number of independent olive oil samples for each group (between 2 and 4). Indeed, when the number of samples is small, LOO-CV procedure has proven to be an adequate procedure to test model prediction capability and to minimize the risk of overoptimistic predictive model performance [3,25,40].…”

“…Zorzal) algorithm selected seven repeated sensors, with the same membrane composition. The inclusion of repeated sensors could be justified by their slight different physical properties due to the possible inhomogeneous membrane surface, which could be attributed to the drop-by-drop membrane preparation technique [40]. On the other hand, the inclusion of repeated sensors in a multivariate model may increase its qualitative and/or quantitative performance [48].…”

“…On the whole, 88 assays were carried out (22 samples of eight EVOO × 2 bottles × 1 extraction of each bottle × 2 analysis), each providing 40 potentiometric signals, varying from -0.03 V to +0.25 V (20 different sensor membranes used in duplicate: S1:1-S1:20 and S2:1-S2:20, as previously discussed [3,40]). Since the voltage signals, recorded during the analysis of the hydroethanolic extracts of the monovarietal EVOO studied, are similar for all sensors and the respective range of variation is relatively narrow, as shown in Fig.…”

Gliadins in Foods and the Electronic Tongue

“…All sensors showed a quantitative response toward gliadin concentration (0.967 ≤ R ≤ 0.997) enabling the quantification of gliadin in standard solutions. For more complex matrices, such as foodstuffs, the possible quantification of gliadin content must be experimentally evaluated, but it is expected that the use of multivariate regression models (linear or nonlinear) based on a subset of the most informative sensors (chosen using a heuristic or a metaheuristic variable selection algorithm) will overcome possible modeling difficulties, namely due to signal interferences (Dias et al, 2014).…”